Results 1 to 10 of about 245,585 (258)
The Annals of Applied Statistics, 2011 We propose a computationally intensive method, the random lasso method, for variable selection in linear models. The method consists of two major steps.
Nan, Bin +3 more
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Hi-LASSO: High-Dimensional LASSO [PDF]
IEEE Access, 2019 High-throughput genomic technologies are leading to a paradigm shift in research of computational biology. Computational analysis with high-dimensional data and its interpretation are essential for the understanding of complex biological systems.
Youngsoon Kim +4 more
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Biofilm, 2023 The International Space Station (ISS) Water Processor Assembly (WPA) experiences intermittent dormancy in the WPA wastewater tank during water recycling events which promotes biofilm formation within the system.
Angie Diaz +6 more
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Life, 2021 The establishment of steady-state continuous crop production during long-term deep space missions is critical for providing consistent nutritional and psychological benefits for the crew, potentially improving their health and performance.
Mary E. Hummerick +13 more
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BMC Microbiology, 2021 Background Seed sanitization via chemical processes removes/reduces microbes from the external surfaces of the seed and thereby could have an impact on the plants’ health or productivity.
Anirudha R. Dixit +11 more
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Frontiers in Plant Science, 2023 Outside the protection of Earth’s magnetic field, organisms are constantly exposed to space radiation consisting of energetic protons and other heavier charged particles.
Anirudha R. Dixit +8 more
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Biometrika, 2020 Summary The properties of penalized sample covariance matrices depend on the choice of the penalty function. In this paper, we introduce a class of nonsmooth penalty functions for the sample covariance matrix and demonstrate how their use results in a grouping of the estimated eigenvalues.
Tyler, David E., Yi, Mengxi
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The reciprocal Bayesian LASSO [PDF]
Statistics in Medicine, 2021 AbstractA reciprocal LASSO (rLASSO) regularization employs a decreasing penalty function as opposed to conventional penalization approaches that use increasing penalties on the coefficients, leading to stronger parsimony and superior model selection relative to traditional shrinkage methods.
Himel Mallick +3 more
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Development of THC estimation model using FTIR spectrum
Nihon Kikai Gakkai ronbunshu, 2021 A novel total hydrocarbon (THC) emission concentration estimation model is proposed for reduction of engine development cost as well as simplification of measurement system.
Hirotaka YABUSHITA +3 more
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Regularized Machine Learning Models for Prediction of Metabolic Syndrome Using GCKR, APOA5, and BUD13 Gene Variants: Tehran Cardiometabolic Genetic Study [PDF]
Cell Journal, 2023 Objective: Metabolic syndrome (MetS) is a complex multifactorial disorder that considerably burdens healthcaresystems. We aim to classify MetS using regularized machine learning models in the presence of the risk variants ofGCKR, BUD13 and APOA5, and ...
Nadia Alipour +5 more
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